This invention relates to a color correcting parameter calculator, an image color correcting device, a method of calculating color correcting parameters in the color correcting parameter calculator, and a program for use in executing the method.
With development of color image devices, it is a recent trend that a high image quality technique of a color image has been important more and more. Especially, strict requirements have been imposed on colors and the image quality has greatly depended on the colors reproduced by color image devices. For example, it has been said that facial skin color, green foliage, and blue sky in a natural image are very significant for a human being. This shows that the image quality can be improved by desirably reproducing such colors.
A correction method is proposed in Japanese Patent Unexamined Publication No. Hei 10-198795 (namely, 198795/1988) so as to reproduce specific objects of facial skin color, green, blue into desirable colors for a human being. The above-mentioned Japanese Patent Unexamined Publication No. Hei 10-198795 corresponds to U.S. Pat. No. 6,229,580 and will be referred to as first reference. In the correction method that may be referred to as a selective color correction method, a color correcting calculation algorithm is used to calculate a selective color correction factor or degree. With this method, it is possible to carry out color correction processing only about a specific hue without changing any other colors except the color in question to be corrected.
A RGB correction formula used in correcting each of specific hues as mentioned above is given by:(R′, G′, B′)=(R, G, B)+hx−(r,g,b),  (1)
where (R, G, B) represent input RGB values included in an input image; (R′, G′, B′), RGB values after correction; and (r, g, b), RGB correction values. In addition, hx is representative of a distance between a center color (Rc, Gc, Bc) to be corrected and an input color (R, G, B) and serves as a parameter (or a color approximation degree) for controlling strength of correction and is given by:hx=[(pos(m−/Hue−h/))/m]×s×v  (2)
where pos (x) takes 0, if x<0, and takes x, if x ≧0; m represents an acceptable hue range; Hue represents Hue values of HSV calculated from the center color to be corrected; h, s, v represent HSV values corresponding to input RGB values.
In order to realize a preferred color reproduction, the RGB correction values (r, g, b) in the formula (1) and the acceptable hue range (m) in the formula (2) should be set to optimum values and range, respectively, in consideration of a hue of a typical color to be corrected. The RGB correction values (r, g, b) and the acceptable hue range (m) may be called color correction parameters. Among these color correction parameters, the RGB values (r, g, b) are more important which serve to change a color to be corrected into a desired color. Such RGB values (r, g, b) are adjusted and determined by an operator, who is watching an input image, in the method disclosed in Japanese Patent Unexamined Publication No. Hei 10-198795.
Besides the above-reference, various methods have been also offered so as to correct a color in an object zone in an image, for example, in Japanese Unexamined Patent Publication No. Hei 11-17969 (17969/1999), Hei 6-133329 (133329/1994), and Hei 6-121159 (121159/1994). In the above-mentioned methods, an operator adjusts the color correction parameters so that a correction object comes to a preferred color, actually watching and confirming an image on a color display device. In other words, color correction is manually executed.
Now, let a huge amount of color images be present. In this case, a very long time and enormous labor are required to process these color images. Moreover, such manual operation results in a variation of an image quality in dependency upon operator's skills. Automatic processing that dispenses with any manual operation would be needed so as to solve the above-mentioned problem.
On the other hand, proposal has been offered about a method of automatically correcting a color of an object zone into a preferred color. For example, such a method is disclosed in a paper (pages 9 to 12) contributed by the instant inventor and etc., to Color Forum Japan 2000 (Nov. 15, 2000) and entitled “Automatic color correction method for Preferred Color Reproduction”.
Specifically, the method disclosed in the above-mentioned paper is featured by the steps of automatically extracting a typical or representative color from a correction object zone and assigning optimum color correction parameters in consideration of hue, brightness, and chroma (or saturation) of the extracted typical color.
Herein, optimum color correction parameters of a typical color, as mentioned above, can be calculated by a method disclosed in Japanese Patent Unexamined Publication No. Hei 11-267937 (267937/1999) that would be referred to as second reference. Herein, it is assumed that the method disclosed in the second reference is applied to the first reference. In this event, provision is made about a great number of image sets for learning and selection is done about a typical color in each correction object zone of the images. Under the circumstances, subjective evaluation is performed so as to obtain two color correction parameters, such as the RGB correction values (r, g, b) and the acceptable hue range m, and to attain combinations of the typical colors and the color correction parameters.
A hue distribution range in which each typical color falls is determined from each hue of the typical colors and is divided into hue divided region at a certain distance. The color correction parameters to be assigned to each hue divided region are obtained by calculating each typical color in the hue divided region with reference to their hues, by getting color correction parameters corresponding to each typical hue, and by statistically processing them.
In FIG. 1, a hue distribution range in which a correction object might fall is divided into a plurality of hue divided regions to which color correction parameters are assigned.
The method disclosed in the first reference is advantageous in that significant object colors for a human being, such as facial skin color, green foliage, blue of sky, can be adjusted by an operator to obtain adjusted effects of color correction and the adjusted effects can be visibly and automatically reflected on a corrected image.
The color correction parameters in the above-mentioned methods are obtained by preparing a calibrated reference color image device, by carrying out subjective evaluation experiments, and by statistically processing results of the subjective evaluation experiments. This shows that the color correction parameters largely depend on color characteristics of the reference color image device. From this fact, it is readily understood that desirable color correction effects can not be always accomplished when the above-mentioned method is applied to any other color image devices that have color characteristics of white and the like different from those of the reference color image device.
The above-mentioned method of automatically correcting colors in the specific object zone is effective to correct colors in the specific object zone of a natural image displayed on the reference color image device. However, no consideration is made at all about calculating color correction parameters suitable for any other color image devices that have different color characteristics from the reference color image device.
Similar problems take place also in the above-referenced publications, such as Japanese Patent Unexamined Publication Nos. Hei 10-198795, Hei 11-17969, Hei 6-133329, and Hei 6-121159.
Practically, color correction should be carried out when a variation of color characteristics is caused to occur in the other color image devices except the reference color image device. In this event, it is necessary to calculate new or updated color correction parameters in connection with the other color image devices also so as to accomplish color correction effects similar to those on the reference color image device.
Heretofore, subjective evaluation experiments have been performed to calculate color correction parameters each time when the color characteristics are changed in each color image device. Such subjective evaluation experiments are laborious and time-consuming.
In any event, no proposal has been made about a method of calculating color correction parameters in connection with different color image devices from the reference color image device. Moreover, no consideration has been made at all about effectively utilizing the color correction parameters adjusted to the reference color image device.